Manager, Data Engineering

Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber, they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn’t like it used to be—the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That’s why we put the power and flexibility in their hands to run their businesses how, where, and when they want!

Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada’s Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail’s Canada’s Top Growing Companies list, and Deloitte Canada’s Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we’ve come a long way from our first customer in 2011—but we’ve just scratched the surface of what we want to accomplish for our customers.

We help employees grow professionally; we have a ton of onboarding resources, tutorials, hackathons, and buddies to support learning and provide opportunities to innovate. We have a range of experience levels on teams which allows for mentor/mentee opportunities. Leaders at Jobber work with empathy and support employees to build healthy work-life harmony. Bring your dedication and passion to this job to fulfill your goals.

The Team:

The Data Integration team’s mission is to empower teams across Jobber with the right data, at the right time, in the right place so they can deliver business value better and faster. Key responsibilities of this team include data ingestion, data activation (egress), platform administration, self-serve tooling, plus data integrity and governance.

The role:

Reporting to the Director of Data, the Manager, Data Engineering will lead a team of data engineers. You will also partner with the team’s Technical Program Manager to prioritize initiatives and collaborate on building quarterly roadmaps. This role’s scope is large as it spans both Data and ML platforms.

A key aspect of this role is managing the team’s performance, supporting individual growth, ensuring high-quality deliverables, and scaling the team as needed. You will also play a key role in shaping technical decisions, collaborating with technical leads, principals, and distinguished engineers.

The Manager, Data Engineering will:

• Live and breathe performance facilitation by helping your team master their craft while collaborating to build extraordinary experiences and systems.

• Be committed to your people’s success by setting goals, holding regular 1-on-1s, providing constructive feedback, and mentoring team members to grow their careers.

• Develop and scale a world-class team by recruiting top talent, leveling up internal capabilities, and implementing processes that improve delivery and collaboration.

• Own the strategy, roadmap, and delivery of high-performance, scalable, and cost-efficient data infrastructure including data stores, compute engines, and orchestration systems.

• Ensure data systems are resilient, observable, and governed. Implementing robust recovery strategies, proactive monitoring, and best practices for security, integrity, and compliance.

• Partner across engineering, analytics, and go-to-market teams to deliver well-structured, high-quality product data and build tools, automation, and solutions that accelerate workflows and create impactful outcomes for Jobber’s small business customers.

• Drive innovation and efficiency with the use of AI tools to support the data strategy. Enable the team to continuously explore, experiment, and improve the state of Data tools with the help of AI.

To be successful, you should have:

• Proven experience managing engineering teams - ideally in data engineering domains - with a track record of delivering high-quality software and data solutions.

• A strong technical foundation in software and data engineering, including distributed data systems, orchestration frameworks, cloud infrastructure, performance tuning, scaling strategies, and cost optimization.

• Hands-on experience in systems design, SQL, modern data tools, and data best practices, including modeling, governance, and quality management.

• Experience implementing observability frameworks, SLAs, disaster recovery strategies, and other practices to ensure resilient, reliable, and compliant data systems.

• The ability to lead and adapt in an agile environment, fostering a culture of continuous learning, critical thinking, and creative problem-solving.

• Excellent collaboration and communication skills, with the ability to work cross-functionally with engineering, product, analytics, and data science teams while mentoring and coaching direct reports.

• Strategic thinking and roadmap planning capabilities, with experience shaping infrastructure initiatives that have measurable impact.

• Strong leadership and mentorship skills, using your experience to guide, influence, and provide constructive feedback to direct reports—ensuring their growth and enabling the team to exceed its goals.

• Highly desired, but not a dealbreaker:

• Hands-on experience with modern data stack tools such as Redshift, Trino, dbt, Airflow, Kafka, and familiarity with data processing frameworks such as Spark and Ray.

• Background in building internal developer platforms, self-service data tooling, or workflow automation for data teams.

• Sound understanding of lambda and/or kappa architecture, batch and streaming principles, and experience implementing either of the two architectures in a production environment.

• Experience in working with Engineering teams to influence upstream data design and instrumentation.

• Exposure to data science and machine learning workflows and their infrastructure requirements.